title: Comparison of an automated respiratory systolic variation test with dynamic preload indicators to predict fluid responsiveness after major surgery.
abstract: BACKGROUND
  Predicting the response of cardiac output to volume administration remains an ongoing clinical challenge. The objective of our study was to compare the ability to predict volume responsiveness of various functional measures of cardiac preload. These included pulse pressure variation (PPV), stroke volume variation (SVV), and the recently launched automated respiratory systolic variation test (RSVT) in patients after major surgery.
  
  
  METHODS
  In this prospective study, 24 mechanically ventilated patients after major surgery were enrolled. Three consecutive volume loading steps consisting of 300 ml 6% hydroxyethylstarch 130/0.4 were performed and cardiac index (CI) was assessed by transpulmonary thermodilution. Volume responsiveness was considered as positive if CI increased by >10%.
  
  
  RESULTS
  In total 72 volume loading steps were analysed, of which 41 showed a positive volume response. Receiver operating characteristic (ROC) curve analysis revealed an area under the curve (AUC) of 0.70 for PPV, 0.72 for SVV and 0.77 for RSVT. Areas under the curves of all variables did not differ significantly from each other (P>0.05). Suggested cut-off values were 9.9% for SVV, 10.1% for PPV, and 19.7° for RSVT as calculated by the Youden Index.
  
  
  CONCLUSIONS
  In predicting fluid responsiveness the new automated RSVT appears to be as accurate as established dynamic indicators of preload PPV and SVV in patients after major surgery. The automated RSVT is clinically easy to use and may be useful in guiding fluid therapy in ventilated patients.
authors.affiliation: Department of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, Cardiovascular Research Center, University Medical Center Hamburg-Eppendorf, Martinistr. 52, D-20246 Hamburg, Germany.
authors.forename: C J C
authors.initials: CJ
authors.lastname: Trepte
authors.forename: V
authors.initials: V
authors.lastname: Eichhorn
authors.forename: S A
authors.initials: SA
authors.lastname: Haas
authors.forename: K
authors.initials: K
authors.lastname: Stahl
authors.forename: F
authors.initials: F
authors.lastname: Schmid
authors.forename: R
authors.initials: R
authors.lastname: Nitzschke
authors.forename: A E
authors.initials: AE
authors.lastname: Goetz
authors.forename: D A
authors.initials: DA
authors.lastname: Reuter
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000403:Airway Resistance; D000465:Algorithms; D000768:Anesthesia, General; D062186:Arterial Pressure / Q000502:physiology; D001331:Automation; D001794:Blood Pressure / Q000502:physiology*; D002302:Cardiac Output / Q000502:physiology; D005260:Female; D005440:Fluid Therapy / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D011182:Postoperative Care / Q000379:methods*; D011184:Postoperative Period; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D015656:Respiratory Mechanics / Q000502:physiology*; D013318:Stroke Volume / Q000502:physiology; D013815:Thermodilution; D055815:Young Adult
keywords: dynamic haemodynamic monitoring; heart–lung interaction; volume responsiveness